where \( \mathrm{x}=0 \) represents \( 1994, \mathrm{x}=1 \) represents 1995 , and so on, and let \( \mathrm{y} \) represent the egg production (in billions). Predict egg production in 2000.
\begin{tabular}{|c|c|}
\hline Year & \( \begin{array}{c}\text { Egg production } \\
\text { (in billions) }\end{array} \) \\
\hline 1994 & 51.7 \\
\hline 1995 & 52.5 \\
\hline 1996 & 54.4 \\
\hline 1997 & 57.3 \\
\hline 1998 & 60.4 \\
\hline 1999 & 63.9 \\
\hline 2000 & 69.6 \\
\hline
\end{tabular}
The linear model for the data is
(Type your answer in slope-intercept form. Use integers or decimals for any numbers in the equation. Round to three decimal places as needed.)
What is the predicted egg production in \( 2000 ? \)
billion
(Type an integer or a decimal. Round to two decimal places as needed.)
Answer
Predicted egg production in 2000: \( y = 2.44(6) + 51.7 = 66.34 \)
Step 1 ：Given linear model: \( y = mx + b \), find \(m\) and \(b\).
Step 2 ：Using data from 1994 and 1999: \( m = \frac{63.9 - 51.7}{5 - 0} = 2.44 \) and \( b = 51.7 \).
Step 3 ：Predicted egg production in 2000: \( y = 2.44(6) + 51.7 = 66.34 \)
